This course provides an accessible introduction to artificial intelligence (AI) through a comparative analysis of A.I. and human intelligence and hands-on programming in Python. Students will explore the historical foundations of A.I. and learn the fundamental concepts, algorithms, and applications that power modern AI systems. In addition students will gain practical experience using popular Python libraries such as NumPy, pandas, scikit-learn, TensorFlow, and NLTK. Through guided labs and interactive examples, learners will implement simple AI models for data-driven decision making. Emphasis is placed on understanding and designing intelligent systems.

Asynchronous.

COGSCI 110 is recommended but not required as a co-requisite for this course.

Repeat Rules

Course is not repeatable for credit.